Human pharmacokinetic characterization and in vitro study of the interaction between doxorubicin and paclitaxel in patients with breast cancer

PURPOSE: We performed a pharmacologic investigation of paclitaxel (PTX) infused over 3 hours and bolus doxorubicin (DOX) to assess the role of sequence, interval between drugs, and duration of doxorubicin infusion on paclitaxel and anthracycline plasma disposition. We also explored possible mechanisms of pharmacokinetic interference involving the physiologic role of the multidrug resistance phenotype in anthracycline and taxane biliary excretion. PATIENTS AND METHODS: Pharmacokinetics was performed in 80 cycles and 36 women with previously untreated metastatic breast cancer. PTX, DOX, and their metabolites 6 alpha-hydroxyl-PTX (6 alpha OH-PTX) and doxorubicinol (DOL) were measured by high-pressure liquid chromatography (HPLC). Human breast cancer MCF-7 wild-type (WT) and resistant (TH) cell lines were cultured in whole human plasma to study anthracycline retention after treatment with different combinations of PTX, Cremophor EL (CEL) (PEG35 castor oil; BASF, Parsippany, NJ), and DOX. RESULTS: Pharmacokinetic interference between PTX and DOX was responsible for nonlinearity of DOX plasma disposition and increased concentrations of DOX and DOL. These effects were PTX dose-dependent, DOX concentration-dependent, and likely a result of interference at the level of liver elimination. In view of the physiologic role of P-glycoproteins (P-gp) in xenobiotic biliary excretion, retention of DOX was assessed in MCF-7 WT and MCF-7 TH cells. Intracellular was significantly higher in MCF-7 WT than MCF-7 TH (P < .05). However, concomitant exposure to DOX, PTX, and CEL caused similar DOX retention in both MCF-7 WT and TH cells. CONCLUSION: PTX, as clinically formulated in CEL, is responsible for a nonlinear disposition of DOX and DOL. Nonlinearity is PTX- and DOX-dependent, and possibly caused by competition for biliary excretion of taxanes and anthracyclines mediated by P-gp. Nonlinearity indicates that even minor modifications of dose and infusion duration of DOX and PTX may lead to unpredictable pharmacodynamic consequences. The postulated role of P-gp suggests that CEL is clinically active, and advises caution in designing combinations of PTX with other drugs that are substrate for P-gp.     

Assessing the reTweet proneness of tweets: predictive models for retweeting

The problem of assessing the mechanisms underlying the phenomenon of virality of social network posts is of great value for many activities, such as advertising and viral marketing, influencing and promoting, early monitoring and emergency response. Among the several social networks, Twitter.com is one of the most effective in propagating information in real time, and the propagation effectiveness of a post (i.e., tweet) is related to the number of times the tweet has been retweeted. Different models have been proposed in the literature to understand the retweet proneness of a tweet (tendency or inclination of a tweet to be retweeted). In this paper, a further step is presented, thus several features extracted from Twitter data have been analyzed to create predictive models, with the aim of predicting the degree of retweeting of tweets (i.e., the number of retweets a given tweet may get). The main goal is to obtain indications about the probable number of retweets a tweet may obtain from the social network. In the paper, the usage of the classification trees with recursive partitioning procedure for prediction has been proposed and the obtained results have been compared, in terms of accuracy and processing time, with respect to other methods. The Twitter data employed for the proposed study have been collected by using the Twitter Vigilance study and research platform of DISIT Lab in the last 18 months. The work has been developed in the context of smart city projects of the European Commission RESOLUTE H2020, in which the capacity of communicating information is fundamental for advertising, promoting alerts of civil protection, etc.     

A classification approach to efficient global optimization in presence of non-computable domains

Gaussian-Process based optimization methods have become very popular in recent years for the global optimization of complex systems with high computational costs. These methods rely on the sequential construction of a statistical surrogate model, using a training set of computed objective function values, which is refined according to a prescribed infilling strategy. However, this sequential optimization procedure can stop prematurely if the objective function cannot be computed at a proposed point. Such a situation can occur when the search space encompasses design points corresponding to an unphysical configuration, an ill-posed problem, or a non-computable problem due to the limitation of numerical solvers. To avoid such a premature stop in the optimization procedure, we propose to use a classification model to learn non-computable areas and to adapt the infilling strategy accordingly. Specifically, the proposed method splits the training set into two subsets composed of computable and non-computable points. A surrogate model for the objective function is built using the training set of computable points, only, whereas a probabilistic classification model is built using the union of the computable and non-computable training sets. The classifier is then incorporated in the surrogate-based optimization procedure to avoid proposing new points in the non-computable domain while improving the classification uncertainty if needed. The method has the advantage to automatically adapt both the surrogate of the objective function and the classifier during the iterative optimization process. Therefore, non-computable areas do not need to be a priori known. The proposed method is applied to several analytical problems presenting different types of difficulty, and to the optimization of a fully nonlinear fluid-structure interaction system. The latter problem concerns the drag minimization of a flexible hydrofoil with cavitation constraints. The efficiency of the proposed method compared favorably to a reference evolutionary algorithm, except for situations where the feasible domain is a small portion of the design space.     

Effect of thermal history on water sorption,elastic properties and the glass transition of epoxy resins

The DGEBA/TETA (diglycidyl ether of bisphenol-A/triethylene tetramine) system was examined in postcuring conditions at 100°C for 3 and 6 days. Sorption kinetics and equilibria at different temperatures and mechanical tests have been performed on the two sets of samples. Thermal treatment of the epoxy resin containing sorbed water affects its subsequent water sorption characteristics, elastic modulus and glass transition temperature. Attention has also been given to the effects on solubility on thermal history in the presence of water. It was observed that the saturation values in such systems are determined once the higher temperature of the thermal cycle is defined. The differences in solubility of samples with different hygrothermal history are explained in terms of microcavities that can be formed by effect of crazing in the plasticized system exposed to high temperatures.     

Tomographic inversion of ocean bottom seismograph (OBS) data: Problems and solutions applied to the NW Svalbard Hydratech data set

The paper is aimed at discussing some problems that may arise in the tomographic inversion of data acquired with particular geometries, as vertical seismic profiles (VSP) or implying the use of Ocean Bottom Seismographs (OBS), and presenting the solutions used to solve them. One problem is due to the limited number of sensors (that may be even a single one) and of their sparseness. This affects the information distribution that is concentrated in the vicinity of each sensor. This fact, together with the second problem, i.e. the strong asymmetry of the ray path, may decrease the reliability of the inversion.Two procedures for irregular adaptive gridding of the reflecting interfaces and single ray datuming are proposed as possible solutions to overcome these obstacles, while obtaining a reliable and highly resolved velocity model in depth: the relative procedures are tested through synthetic models and on real data.     

A control theoretic approach to malaria immunotherapy with state jumps

We investigate a control method for malaria dynamics to boost the immune response using a model-based approach. The idea of state jump is introduced and discussed using a hybrid model. To implement the state jumps we use a physiologically feasible method for the biological system, whereby the introduction of a pathogen into the system steers it to a desirable status. It is noted that we take advantage of a pathogen to implement state jumps in the system. The study is supported by recently reported experimental results.     

Expression of α-amylase inhibitors in diploid Triticum species

The aim of the work was to characterize the expression of various α-amylase inhibitors (αAIs), well known anti-nutritional compounds, for the development of healthier diploid wheat-based functional foods.